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<li class="navelem"><a class="el" href="namespaceekf.html">ekf</a></li><li class="navelem"><a class="el" href="structekf_1_1ekf__param.html">ekf_param</a></li>  </ul>
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<p>Structure holding the parameters of the statistical linearization.  
 <a href="structekf_1_1ekf__param.html#details">More...</a></p>

<p><code>#include &lt;<a class="el" href="ekf__types_8h_source.html">ekf_types.h</a>&gt;</code></p>
<table class="memberdecls">
<tr class="heading"><td colspan="2"><h2 class="groupheader"><a name="pub-attribs"></a>
Public Attributes</h2></td></tr>
<tr class="memitem:a9b71dc086b83e78c78f6258ce19fafb4"><td class="memItemLeft" align="right" valign="top"><a class="el" href="classekf_1_1EvolutionNoise.html">EvolutionNoise</a> *&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="structekf_1_1ekf__param.html#a9b71dc086b83e78c78f6258ce19fafb4">evolution_noise</a></td></tr>
<tr class="memdesc:a9b71dc086b83e78c78f6258ce19fafb4"><td class="mdescLeft">&#160;</td><td class="mdescRight">Evolution noise type.  <a href="#a9b71dc086b83e78c78f6258ce19fafb4">More...</a><br/></td></tr>
<tr class="separator:a9b71dc086b83e78c78f6258ce19fafb4"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a931255569a953be75868b7ef098ff310"><td class="memItemLeft" align="right" valign="top">double&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="structekf_1_1ekf__param.html#a931255569a953be75868b7ef098ff310">observation_noise</a></td></tr>
<tr class="memdesc:a931255569a953be75868b7ef098ff310"><td class="mdescLeft">&#160;</td><td class="mdescRight">Covariance of the observation noise.  <a href="#a931255569a953be75868b7ef098ff310">More...</a><br/></td></tr>
<tr class="separator:a931255569a953be75868b7ef098ff310"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:afc3c7b95fe943c99c49e7b0c5703de68"><td class="memItemLeft" align="right" valign="top">double&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="structekf_1_1ekf__param.html#afc3c7b95fe943c99c49e7b0c5703de68">prior_pk</a></td></tr>
<tr class="memdesc:afc3c7b95fe943c99c49e7b0c5703de68"><td class="mdescLeft">&#160;</td><td class="mdescRight">Prior estimate of the covariance matrix.  <a href="#afc3c7b95fe943c99c49e7b0c5703de68">More...</a><br/></td></tr>
<tr class="separator:afc3c7b95fe943c99c49e7b0c5703de68"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a1246cf99fd3c8a31199c74c2ebc96574"><td class="memItemLeft" align="right" valign="top">int&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="structekf_1_1ekf__param.html#a1246cf99fd3c8a31199c74c2ebc96574">n</a></td></tr>
<tr class="memdesc:a1246cf99fd3c8a31199c74c2ebc96574"><td class="mdescLeft">&#160;</td><td class="mdescRight">Number of parameters to estimate.  <a href="#a1246cf99fd3c8a31199c74c2ebc96574">More...</a><br/></td></tr>
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<tr class="memitem:a1430eac7209095599a396000fc31ec8c"><td class="memItemLeft" align="right" valign="top">int&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="structekf_1_1ekf__param.html#a1430eac7209095599a396000fc31ec8c">no</a></td></tr>
<tr class="memdesc:a1430eac7209095599a396000fc31ec8c"><td class="mdescLeft">&#160;</td><td class="mdescRight">Dimension of the output.  <a href="#a1430eac7209095599a396000fc31ec8c">More...</a><br/></td></tr>
<tr class="separator:a1430eac7209095599a396000fc31ec8c"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a8e3a67547cde4646e17689a669fb25bc"><td class="memItemLeft" align="right" valign="top">bool&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="structekf_1_1ekf__param.html#a8e3a67547cde4646e17689a669fb25bc">observation_gradient_is_diagonal</a></td></tr>
<tr class="memdesc:a8e3a67547cde4646e17689a669fb25bc"><td class="mdescLeft">&#160;</td><td class="mdescRight">Is the observation gradient diagonal ? In that case, simplifications can be introduced.  <a href="#a8e3a67547cde4646e17689a669fb25bc">More...</a><br/></td></tr>
<tr class="separator:a8e3a67547cde4646e17689a669fb25bc"><td class="memSeparator" colspan="2">&#160;</td></tr>
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<a name="details" id="details"></a><h2 class="groupheader">Detailed Description</h2>
<div class="textblock"><p>Structure holding the parameters of the statistical linearization. </p>
<dl><dt><b>Examples: </b></dt><dd><a class="el" href="example-009_8cc-example.html#_a0">example-009.cc</a>.</dd>
</dl></div><h2 class="groupheader">Member Data Documentation</h2>
<a class="anchor" id="a9b71dc086b83e78c78f6258ce19fafb4"></a>
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          <td class="memname"><a class="el" href="classekf_1_1EvolutionNoise.html">EvolutionNoise</a>* ekf::ekf_param::evolution_noise</td>
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<p>Evolution noise type. </p>
<dl><dt><b>Examples: </b></dt><dd><a class="el" href="example-009_8cc-example.html#a7">example-009.cc</a>.</dd>
</dl>
</div>
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          <td class="memname">int ekf::ekf_param::n</td>
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<p>Number of parameters to estimate. </p>
<dl><dt><b>Examples: </b></dt><dd><a class="el" href="example-009_8cc-example.html#a3">example-009.cc</a>.</dd>
</dl>
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<p>Dimension of the output. </p>
<dl><dt><b>Examples: </b></dt><dd><a class="el" href="example-009_8cc-example.html#a4">example-009.cc</a>.</dd>
</dl>
</div>
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          <td class="memname">bool ekf::ekf_param::observation_gradient_is_diagonal</td>
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<p>Is the observation gradient diagonal ? In that case, simplifications can be introduced. </p>
<dl><dt><b>Examples: </b></dt><dd><a class="el" href="example-009_8cc-example.html#a10">example-009.cc</a>.</dd>
</dl>
</div>
</div>
<a class="anchor" id="a931255569a953be75868b7ef098ff310"></a>
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          <td class="memname">double ekf::ekf_param::observation_noise</td>
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</div><div class="memdoc">

<p>Covariance of the observation noise. </p>
<dl><dt><b>Examples: </b></dt><dd><a class="el" href="example-009_8cc-example.html#a8">example-009.cc</a>.</dd>
</dl>
</div>
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          <td class="memname">double ekf::ekf_param::prior_pk</td>
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</div><div class="memdoc">

<p>Prior estimate of the covariance matrix. </p>
<dl><dt><b>Examples: </b></dt><dd><a class="el" href="example-009_8cc-example.html#a9">example-009.cc</a>.</dd>
</dl>
</div>
</div>
<hr/>The documentation for this struct was generated from the following file:<ul>
<li>/home/fix_jer/SVN/easykf_trunk/trunk/easykf-2.04/src/<a class="el" href="ekf__types_8h_source.html">ekf_types.h</a></li>
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